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Chair of Visual Computing
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  1. Friedrich-Alexander-Universität
  2. Technische Fakultät
  3. Department Informatik

Chair of Visual Computing

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  • Research
    • Rendering and Visualization
    • Geometric Modeling and 3D Reconstruction
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    • Visual Computing for Digital Humanities and Social Sciences
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    • Vertiefungsrichtung Visual Computing
    • Summer Term 2025
    • Winter Term 2024/25
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  2. Publications
  3. Automated Heart Localization in Cardiac Cine MR Data

Automated Heart Localization in Cardiac Cine MR Data

In page navigation: Publications
  • Adaptive stray-light compensation in dynamic multi-projection mapping
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  • Analytic Displacement Mapping using Hardware Tessellation
  • Anisotropic Surface Based Deformation
  • Auto-Calibration for Dynamic Multi-Projection Mapping on Arbitrary Surfaces
  • Automated Heart Localization in Cardiac Cine MR Data
  • Demo of Face2Face: Real-time Face Capture and Reenactment of RGB Videos
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  • HeadOn: Real-time Reenactment of Human Portrait Videos
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  • State of the Art Report on Real-time Rendering with Hardware Tessellation
  • Stray-Light Compensation in Dynamic Projection Mapping
  • Visualization and Deformation Techniques for Entertainment and Training in Cultural Heritage
  • VolumeDeform: Real-time Volumetric Non-rigid Reconstruction

Automated Heart Localization in Cardiac Cine MR Data


 

  • Hoffmann R., Kranz F., Siegl C., Janka RM., Grosso R., Greiner G.:
    Automated Heart Localization in Cardiac Cine MR Data
    In: Bildverarbeitung für die Medizin 2016, Springer, 2016, p. 116--121
    DOI: 10.1007/978-3-662-49465-3_22
    BibTeX: Download

Cardiac MRI is the modality of choice in cardiology for the assessment of the ventricular function, since the heart’s anatomy is visualized with high resolution. This functional assessment is a time-consuming task for the cardiac radiologist when performed manually. Therefore, computer-driven diagnostic solutions are of particular importance for clinical applications. In order to ensure the success of such computer aided diagnosis algorithms however, a correct, initial localisation of the heart region in the raw data is crucial. For this purpose, we present a novel, simple and fully automated approach for localizing the heart region in cardiac cine MR data. Without the need for prior knowledge or training datasets, this method enables a ready to use application for a robust localization. This processing step is a fundamental component for the development of integrated automated applications.

Chair of Visual Computing
(Lehrstuhl für Graphische Datenverarbeitung)

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91058 Erlangen
Deutschland
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